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Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics
In the case of using an oracle policy, it can be unclear how best to incorporate the oracle policy's experience into the learning policy in a way that maximizes learning sample efficiency.
Differential radial basis function network for sequence modelling
We propose a differential radial basis function (RBF) network termed RBF-DiffNet -- whose hidden layer blocks are partial differential equations (PDEs) linear in terms of the RBF -- to make the baseline RBF network robust to noise in sequential data.
Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins
Vehicle climate control systems aim to keep passengers thermally comfortable.
K-Means Clustering using Tabu Search with Quantized Means
Moreover, the difficulty in parameter selection in the existing TS approach does not make it any more attractive.
Linear classifier design under heteroscedasticity in Linear Discriminant Analysis
Under normality and homoscedasticity assumptions, Linear Discriminant Analysis (LDA) is known to be optimal in terms of minimising the Bayes error for binary classification.
